CALL FOR PAPERS
The 12th Workshop on Argument Mining @ ACL 2025
July 31, 2025
https://argmining-org.github.io/2025/

The 12th Workshop on Argument Mining will be held on July 31, 2025, in Viena, Austria, together with ACL 2025.

The Workshop on Argument Mining provides a regular forum for presenting and discussing cutting-edge research in argument mining (a.k.a argumentation mining) for academic and industry researchers. By continuing a series of eleven successful previous workshops, this edition will welcome the submission of long and short papers, as well as extended abstracts and PhD proposals. It will also feature a number of shared tasks and a keynote talk.

IMPORTANT DATES

Direct paper submission deadline (OpenReview): April 17, 2025
Paper commitment from ARR: May 21, 2025
Notification of acceptance: May 28, 2025
Camera-ready papers due: June 4, 2025
Workshop: July 31, 2025


TOPICS OF INTEREST

- Identification, Assessment, and Analysis of Arguments
- Identification of argument components (e.g., premises and conclusions)
- Structure analysis of arguments within and across documents
- Relation Identification between arguments and counterarguments (e.g., support and attack)
- Creation and evaluation of argument annotation schemes, relationships to linguistic and discourse annotations, (semi-) automatic argument annotation methods and tools, and creation of argumentation corpora
- Assessment of arguments for various properties (e.g., stance, clarity)
- Generation of Arguments, Multi-modal and Multi-lingual Argument Mining
- Automatic generation of arguments and their components
- Consideration of discourse goals in argument generation
- Argument mining and generation from multi-modal/multi-lingual data
- Mining and Analysis of different Genres and Domains of Arguments
- Argument mining in specific genres and domains (e.g., education, law, scientific writing)
- Analysis of unique styles within genres (e.g., short informal text, highly structured writing)
- Modelling, assessing, and critically reflecting on the argumentative reasoning capabilities of Large Language Models
- Knowledge Integration, Information Retrieval, and Real-world Applications
- Integration of commonsense and domain knowledge into argumentation models
- Combination of information retrieval methods with argument mining
- Real-world applications, including argument web search, opinion analysis and summarization, and misinformation detection
- Interdisciplinary interfaces of Argument Mining
- Mining political discourse, by experts and laypeople
- Argument mining support for deliberation
- Persuasion and convincingess from a psychological perspective
- Subjectivity, disagreements and perspectivism in argumentation
- Ethical Considerations and Future Reflections
- Reflection on the ethical aspects and societal impact of argument-mining methods
- Reflection on the future of argument mining in light of the fast advancement of large language models (LLMs)


SUBMISSIONS

The organizing committee welcomes submitting long papers, short papers, extended abstracts and PhD proposals. Accepted papers will be presented via oral or poster presentations. Long and short papers will be included in the ACL proceedings as workshop papers. Extended abstracts and PhD proposals will be non-archival.
- Long paper submissions must describe substantial, original, completed, and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Long papers must be at most eight pages, including title, text, figures, and tables. An unlimited number of pages is allowed for references. Two additional pages are allowed for appendices, and an extra page is allowed in the final version to address reviewers’ comments.
- Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead, short papers should have a point that can be made in a few pages, such as a small, focused contribution, a negative result, or an interesting application nugget. Short papers must be at most four pages, including title, text, figures, and tables. An unlimited number of pages is allowed for references. One additional page is allowed for the appendix, and an extra page is allowed in the final version to address reviewers’ comments.
- Extended abstracts must be at most two pages including references describing ongoing projects, interesting pieces of data or results, or already published work.
- PhD proposals must describe PhD projects being or to be developed within the broad field of natural language argumentation processing. PhD proposals must be at most four pages including the main research directions or challenges being investigated, the specific contributions made (on the research direction), and the directions for the remaining work. A dedicated poster session will be hosted, allowing students to get feedback and discuss their work with a broad and multidisciplinary community.


Multiple Submissions
ArgMining 2025 will not consider any paper under review in a journal or another conference or workshop at the time of submission, and submitted papers must not be submitted elsewhere during the review period.

ArgMining 2025 will also accept submissions of ARR-reviewed papers, provided that the ARR reviews and meta-reviews are available by the ARR commitment deadline (May 21). However, ArgMining 2025 will not accept direct submissions that are actively under review in ARR, or that overlap significantly ()25%) with such submissions.

Submission Format
All long, short, and demonstration submissions must follow the two-column ACL 2025 format. Authors are expected to use the LaTeX or Microsoft Word style template (https://github.com/acl-org/acl-style-files). Submissions must conform to the official ACL style guidelines contained in these templates. Submissions must be electronic and in PDF format.


Submission Link and Deadline For Direct Submissions
Authors have to fill in the submission form in the OpenReview system and upload a PDF of their paper before April 17, 2025, 11:59 pm UTC-12h (anywhere on earth).

https://openreview.net/group?id=aclweb.org/ACL/2025/Workshop/ArgMining

For the ARR commitment process, we will provide details in our second call for papers.

Double Blind Review
ArgMining 2025 will follow the ACL policies for preserving the integrity of double-blind review for long and short paper submissions. Papers must not include authors’ names and affiliations. Furthermore, self-references or links (such as GitHub) that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …” must be avoided. Instead, use citations such as “Smith previously showed (Smith, 1991) …” Papers that do not conform to these requirements will be rejected without review. Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use the third person or named reference to this work, as described above (“Smith showed” rather than “we showed”). Papers may be accompanied by a resource (software and/or data) described in the paper, but these resources should also be anonymized.
Unlike long and short papers, demo descriptions will not be anonymous. Demo descriptions should include the authors’ names and affiliations, and self-references are allowed.


ANONYMITY PERIOD (taken from the ACL call for papers in verbatim for the most part)
We follow the ACL Policies for Review and Citation. Submissions must be anonymized, but there is no anonymity period or limitation on posting or discussing non-anonymous preprints while the work is under peer review.


BEST PAPER AWARD
In order to recognize significant advancements in argument mining science and technology, ArgMining 2025 will include the Best Paper award. All papers at the workshop are eligible for the best paper award, and a selection committee consisting of prominent researchers in the fields of interest will select the award recipients.

ArgMining 2025 ORGANIZING COMMITTEE

Elena Chistova, Laboratory for Analysis and Controllable Text Generation Technologies, RAS
Philipp Cimiano, Bielefeld University
Shohreh Haddadan, Machine learning department, Moffitt Cancer Center
Gabriella Lapesa, Leibniz Institute for the Social Sciences (GESIS), Cologne, and Heinrich-Heine University Düsseldorf
Ramon Ruiz-Dolz, Centre for Argument Technology (ARG-tech), University of Dundee